code: def update_equal_and_diff_gaps_diff_sizes(
      prev: int = 0, size=5, gap: int = 1, max_step=100
  ):
      data: analyses.SeriesModel = analyses.series.Series().to_data()
      while prev <= max_step / 2:
          last = prev + size
  
          step = [*range(prev, last, gap)]
          value = random(len(step)).tolist()
  
          prev = step[-1] + gap
  
          s = analyses.series.Series().load(data)
          s.update(step, value)
  
          data = s.to_data()
  
      while prev <= max_step:
          size = randint(1, 6)
          last = prev + size
  
          step = []
          for s in range(size):
              last = last + randint(1, 10)
              step.append(last)
          value = random(len(step)).tolist()
  
          prev = last
  
          s = analyses.series.Series().load(data)
          s.update(step, value)
  
          data = s.to_data()
  
      print(data["step"].tolist())
  
file_path: labml/app/server/unit_tests/series.py
imports: from labml import monit
  from numpy.random import random, randint
  from labml_app.db import analyses
label_desc: Use image node_id 7 for calling a global function with example usage: update_equal_and_diff_gaps_diff_sizes(prev, size, gap, max_step) without return types